杂波抑制的分形处理:小波-多尺度自适应Kalman滤波

Fractal processing for clutter suppression:wavelet-multi-scale adaptive Kalman filter

从杂波分形模型的角度,以基于小波变换和多尺度自适应Kalman滤波的方法,解决雷达信号处理中重要的杂波抑制问题。首先对接收信号作小波分解,利用小波系数建立状态方程和观测方程,用Kalman滤波对每一尺度估计分形杂波,然后从接收信号中减去估计得到的分形杂波,从而实现杂波抑制。仿真结果表明,基于小波变换和多尺度Kalman滤波的处理方法,能对分形杂波进行有效的估计分析,进而实现有效的抑制。

A method of fractional clutter suppression based on wavelet and a multi-scale Kalman filter is proposed. A dynamic system is formulated based on the orthonormal wavelet decomposition coefficients of the received signal. The fractional clutter is estimated using the Kalman filter on each scale. Then, the estimated fractional clutter is subtracted from the received signal. Some simulation results demonstrate the algorithm is effective for the fractional clutter suppression.